4 results match your criteria Advances In Data Analysis And Classification[Journal]

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From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering.

Adv Data Anal Classif 2019 24;13(1):33-64. Epub 2018 Aug 24.

Institute for Statistics and Mathematics, Vienna University of Economics and Business (WU), Welthandelsplatz 1, 1020 Vienna, Austria.

In model-based clustering mixture models are used to group data points into clusters. A useful concept introduced for Gaussian mixtures by Malsiner Walli et al. (Stat Comput 26:303-324, 2016) are sparse finite mixtures, where the prior distribution on the weight distribution of a mixture with components is chosen in such a way that a priori the number of clusters in the data is random and is allowed to be smaller than with high probability. Read More

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http://dx.doi.org/10.1007/s11634-018-0329-yDOI Listing
August 2018
2 Reads

Ensemble of a subset of NN classifiers.

Adv Data Anal Classif 2018 22;12(4):827-840. Epub 2016 Jan 22.

1Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ UK.

Combining multiple classifiers, known as ensemble methods, can give substantial improvement in prediction performance of learning algorithms especially in the presence of non-informative features in the data sets. We propose an ensemble of subset of NN classifiers, ESNN, for classification task in two steps. Firstly, we choose classifiers based upon their individual performance using the out-of-sample accuracy. Read More

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http://dx.doi.org/10.1007/s11634-015-0227-5DOI Listing
January 2016
3 Reads

Improved initialisation of model-based clustering using Gaussian hierarchical partitions.

Adv Data Anal Classif 2015 Dec 26;9(4):447-460. Epub 2015 Oct 26.

Department of Statistics, University of Washington, Box 354322, Seattle, Washington 98195-4322.

Initialisation of the EM algorithm in model-based clustering is often crucial. Various starting points in the parameter space often lead to different local maxima of the likelihood function and, so to different clustering partitions. Among the several approaches available in the literature, model-based agglomerative hierarchical clustering is used to provide initial partitions in the popular mclust R package. Read More

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http://dx.doi.org/10.1007/s11634-015-0220-zDOI Listing
December 2015
17 Reads

Assessing and accounting for time heterogeneity in stochastic actor oriented models.

Adv Data Anal Classif 2011 Jul;5(2):147-176

Department of Statistics, University of Oxford, Oxford, UK. Network Science Center, United States Military Academy, New York, USA.

This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijders (Sociological Methodology. Blackwell, Boston, pp 361-395, 2001) which are meant to study the evolution of networks. SAOMs model social networks as directed graphs with nodes representing people, organizations, etc. Read More

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http://dx.doi.org/10.1007/s11634-010-0076-1DOI Listing
July 2011
5 Reads
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